activity
20212025
most citedEventBERT: A Pre-Trained Model for Event Correlation Reasoning

9 citations · 14 across the 13 of their papers we have counts for

collaborators

22 papers

cs.CV2025

Sim4Seg: Boosting Multimodal Multi-disease Medical Diagnosis Segmentation with Region-Aware Vision-Language Similarity Masks

Lingran Song, Yucheng Zhou, Jianbing Shen

Despite significant progress in pixel-level medical image analysis, existing medical image segmentation models rarely explore medical segmentation and diagnosis tasks jointly. Howe…

cs.AI2025

TheraMind: A Strategic and Adaptive Agent for Longitudinal Psychological Counseling

He Hu, Chiyuan Ma, Qianning Wang +5

The shortage of mental health professionals has driven the web to become a primary avenue for accessible psychological support. While Large Language Models (LLMs) offer promise for…

cs.CL2025

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Weigao Sun, Jiaxi Hu, Yucheng Zhou +12

Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer m…

cs.CL2025

MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration

Yucheng Zhou, Lingran Song, Jianbing Shen

Recent advancements in medical Large Language Models (LLMs) have showcased their powerful reasoning and diagnostic capabilities. Despite their success, current unified multimodal m…

cs.CV2025

ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependencies

Chenglin Wang, Yucheng Zhou, Qianning Wang +2

Text-driven image editing has achieved remarkable success in following single instructions. However, real-world scenarios often involve complex, multi-step instructions, particular…

cs.CV2025

Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation

Yucheng Zhou, Jiahao Yuan, Qianning Wang

Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with comple…